地球信息科学学报 ›› 2014, Vol. 16 ›› Issue (5): 735-745.doi: 10.3724/SP.J.1047.2014.00735

所属专题: 地理大数据

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面向不同主题的犯罪大数据可视分析

李代超(), 吴升*()   

  1. 福州大学 福建省空间信息工程研究中心,福州 350003
  • 收稿日期:2014-02-18 修回日期:2014-04-03 出版日期:2014-09-10 发布日期:2014-09-04
  • 通讯作者: 吴升 E-mail:maplidaichao@gmail.com;ws0110@163.com
  • 作者简介:

    作者简介:李代超(1989-),女,河南人,硕士生,研究方向为信息可视化与可视分析,地图制图理论、方法与技术等。E-mail: maplidaichao@gmail.com

  • 基金资助:
    国家“863”重大项目课题(2012AA12A208)

Theme-Oriented Visual Analysis of Crime with Big Data

LI Daichao(), WU Sheng*()   

  1. Spatial Information Research Center of Fujian, Fuzhou university, Fuzhou 350003, China
  • Received:2014-02-18 Revised:2014-04-03 Online:2014-09-10 Published:2014-09-04
  • Contact: WU Sheng E-mail:maplidaichao@gmail.com;ws0110@163.com
  • About author:

    *The author: CHEN Nan, E-mail:fjcn99@163.com

摘要:

大数据时代,传统犯罪分析将向探索式可视分析的方向转变。本文基于公安犯罪数据的特点和犯罪分析理论,结合可视化技术(Wordle图、故事线图、平行坐标图、散点图矩阵等),从表示内容、表示方法、交互设计等提出面向不同主题的犯罪大数据可视分析方法,其中,包括系列犯罪时空轨迹数据的可视分析、犯罪实时态势数据的可视分析、犯罪时空过程数据的可视分析、时间序列犯罪统计数据的可视分析、犯罪案情文本数据的可视分析、犯罪多维属性数据的可视分析,以及犯罪相关统计数据的可视分析等。相关可视分析方法为案件侦查、犯罪趋势预测、犯罪热点分析等方面提供了支持,也为今后面向其他领域的可视化表达研究提供了借鉴和参考。

关键词: 大数据, 可视分析, 犯罪分析

Abstract:

Information visual analysis is one of the key technologies in big data. The advent of “big data” era promotes the development of visualization techniques and also brings changes to the traditional crime analysis. The crime visualization could offer assistance to crime analysis in practice. However, they are separated in application. The primary challenge that crime visualization faces is how to analyze data features’ heterogeneity, scale, timeliness and complexity. This problem can be resolved by applying visual analysis, which allows users to explore data of different types and dimensions, and to obtain more valuable information with high correlation through interactions. Public security data, in the “big data” era, is characterized by multi-source and heterogeneity, and multi-dimension and long temporal series. Based on the characteristics of the data and criminal analysis theory, this article mainly focuses on the visual content, the representing method and the interactive design of visual crime analysis combined with geo-visualization and information visualization technologies, such as Wordle, Story line, parallel coordinate and scatter plot matrices, etc. A series of topic-oriented visual analyses were proposed in this study, including visual analyses based on spatio-temporal trajectory data of serial crime, real-time criminal data, spatio-temporal data of criminal process, criminal time-series statistical data, descriptive crime texts, criminal multidimensional attribute data, and crime-related statistical data. Supports from criminal cases investigation, trend prediction, hotspot analysis and references of visualizing studies from other fields were also offered and discussed in this article.

Key words: Key Words: big data, visual analysis, crime analysis